湖南电力 ›› 2024, Vol. 44 ›› Issue (6): 10-16.doi: 10.3969/j.issn.1008-0198.2024.06.002

• 特约专栏: 新型电力系统 • 上一篇    下一篇

考虑出力不确定性的分布式光伏优化配置方法

孙贤水, 曾进辉, 刘颉, 苏旨音, 何鹏辉   

  1. 湖南工业大学电气与信息工程学院,湖南 株洲 412007
  • 收稿日期:2024-09-02 出版日期:2024-12-25 发布日期:2024-12-25
  • 通信作者: 孙贤水(2000),男,硕士研究生,研究方向为分布式光伏并网规划。
  • 作者简介:曾进辉(1981),男,教授,博士生导师,主要研究方向为电力电子变换与控制。刘颉(1989),男,博士,硕士生导师,主要研究方向为负荷预测、电能质量检测和多能互补调度。
  • 基金资助:
    国家自然科学基金面上项目(52377185)

An Optimal Allocation Method for Distributed Photovoltaic Considering Output Uncertainty

SUN Xianshui, ZENG Jinhui, LIU Jie, SU Zhiyin, HE Penghui   

  1. Collegeof Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China
  • Received:2024-09-02 Online:2024-12-25 Published:2024-12-25

摘要: 针对分布式光伏布局不合理对配电网造成不可逆转的冲击的问题,提出一种考虑光伏出力不确定性的分布式光伏优化配置模型。该模型以分布式光伏接入容量最大、网络损耗最低为目标函数,求解分布式光伏的最优接入位置和接入容量。求解模型时采用改进的麻雀搜索算法,该算法具有优秀的全局和局部搜索能力、良好的个体更新机制,可以帮助此类模型更加快速准确地找到最优解。IEEE-33节点配电网对该模型的仿真结果表明,采用改进麻雀搜索算法求解该模型可以使分布式光伏做到应接尽接,同时降低配电网的网络损耗,改善配电网的电能质量,实现分布式光伏资源的优化配置。

关键词: 配电网, 分布式光伏, 优化配置, 改进麻雀搜索算法

Abstract: To solve the problem that the unreasonable layout of distributed photovoltaic(PV) will cause irreversible impact on the distribution network, a distributed PV optimal allocation model is proposed which considers the uncertainty of PV output. Meanwhile, the optimal access location and access capacity of distributed PV are solved by taking the maximum access capacity and the lowest network loss as the objective function. The improved sparrow search algorithm is used to solve the model,which has excellent global and local search ability and good individual update mechanism, and can find the optimal solution more quickly and accurately for such models. The simulation results of the model using IEEE-33 node distribution network show that full connection of distributed PV can be achieved through using the improved sparrow search algorithm to solve the model, network losses of the distribution network can be reduced, the power quality of the distribution network can be improved,and optimized allocation of distributed PV resources can be achieved.

Key words: distribution network, distributed photovoltaic, optimized configuration, improved sparrow search algorithm

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